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@血色又残阳 需要语音处理的资料 #50
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参 @钱知易 有没有机器学习和深度学习在多媒体信息检索领域的资源? #39 |
[求助] @血色又残阳 问:需要语音处理的资料 要求 1、论文最好有配套代码,可以跑;2、当前学术界和工业界最新或者主流技术有哪些;3、是否有跟深度学习结合的;4、最好也有说话人鉴别的相关论文和代码。Github上的讨论:http://t.cn/RPimiDz 初步结果见 http://t.cn/RPxj0Yi |
readingshttp://www.signalprocessingsociety.org/technical-committees/list/sl-tc/spl-nl/2013-05/ALIZE/ ALIZE 3.0 - Open-source platform for speaker recognition http://research.microsoft.com/pubs/217165/ICASSP_DeepTextLearning_v07.pdf Deep Learning for http://research.microsoft.com/pubs/189008/tasl-deng-2244083-x_2.pdf Li Deng, Xiao Li, Machine Learning Paradigms for Speech Recognition: An Overview http://research.google.com/pubs/SpeechProcessing.html Google Speech processing http://www.emory.edu/BUSINESS/speech/SpeechRecCase.pdf nuance white paper, business use cases pointers for explorationhttp://en.wikipedia.org/wiki/Speech_recognition http://www.technologyreview.com/news/427793/where-speech-recognition-is-going/ Where Speech Recognition Is Going http://technav.ieee.org/tag/1597/speaker-recognition 48 resources related to Speaker Recognition conferencesPopular speech recognition conferences held each year or two include SpeechTEK and SpeechTEK Europe, ICASSP, Interspeech/Eurospeech, and the IEEE ASRU. Conferences in the field of natural language processing, such as ACL, NAACL, EMNLP, and HLT, are beginning to include papers on speech processing. Important journals include the IEEE Transactions on Speech and Audio Processing (now named IEEE Transactions on Audio, Speech and Language Processing), Computer Speech and Language, and Speech Communication. http://www.interspeech2014.org/public.php?page=tutorial.html tutorial of interspeech 2014 http://www.icassp2014.org/tutorials.html icassp 2014 http://www.speechtek.com/2014/ SpeechTek http://www.iscslp2014.org/public.php?page=keynote.html ISCSLP@INTERSPEECH 2014 - The 9th International Symposium on Chinese Spoken Language Processing |
整理出来一些东西, 还不是很完善, 欢迎提意见 |
[资料整理] 深度学习在语音识别的应用,入门篇: http://memect.co/TPZxK8L 向 @李开复 在CMU做的Sphinx(1988)致敬。介绍几个牛人和顶级团队: 微软 (邓力 Li Deng )和谷歌 (Vincent Vanhoucke, Geoffrey E. Hinton)。 |
1、论文最好有配套代码,可以跑一下对比效果;
2、当前学术界和工业界最新或者主流技术有哪些;
3、是否有跟深度学习结合的;
4、最好也有说话人鉴别的相关论文和代码。
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